Instructions to use Elaina617/rubyhoshino with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Elaina617/rubyhoshino with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Elaina617/rubyhoshino", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 001a6f78ac892322f40214318e00b25ae95d096d116ed529fa554518b2d883ce
- Size of remote file:
- 246 MB
- SHA256:
- f5696af3eab33b692c94911903981ce73432e8bbc1132c79d82fb37ff0bc0b8d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.